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» Bounding Learning Time in XCS
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GECCO
2004
Springer
14 years 22 days ago
Bounding Learning Time in XCS
It has been shown empirically that the XCS classifier system solves typical classification problems in a machine learning competitive way. However, until now, no learning time es...
Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
13 years 11 months ago
Bounding XCS's parameters for unbalanced datasets
This paper analyzes the behavior of the XCS classifier system on imbalanced datasets. We show that XCS with standard parameter settings is quite robust to considerable class imbal...
Albert Orriols-Puig, Ester Bernadó-Mansilla
GECCO
2008
Springer
144views Optimization» more  GECCO 2008»
13 years 8 months ago
Self-adaptive constructivism in Neural XCS and XCSF
For artificial entities to achieve high degrees of autonomy they will need to display appropriate adaptability. In this sense adaptability includes representational flexibility gu...
Gerard David Howard, Larry Bull, Pier Luca Lanzi
GECCO
2007
Springer
186views Optimization» more  GECCO 2007»
14 years 1 months ago
Cascaded generic XCS to learn about reminding preferences
We are developing an adaptive reminding system, which learns when and how to present notifications. In this paper, we focus on our XCS-based model, composed of two cascaded sets ...
Nadine Richard, Samuel Tardieu, Seiji Yamada
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
13 years 8 months ago
Managing team-based problem solving with symbiotic bid-based genetic programming
Bid-based Genetic Programming (GP) provides an elegant mechanism for facilitating cooperative problem decomposition without an a priori specification of the number of team member...
Peter Lichodzijewski, Malcolm I. Heywood